1. THE AUGMENTED ANALYTICS
RESET IN RETAIL

2. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
Retail has undergone a tremendous amount of turmoil in recent years. The Covid-19
pandemic has fundamentally altered the way consumers shop, with current global supply
chain issues only adding to the chaos. Online retail has experienced a huge surge which has
led to challenges around coping with scaling to meet customer demand and issues such as
needing to process a vastly increased number of returns.
As they have become accustomed to doing, retailers have looked to analytics to help
understand the changes they are facing. But the lack of relevant data due to the
unprecedented circumstances means insights have not always been easy to find. Traditional
retail analytics involves examining past behavior in order to infer future behavior – but
existing algorithms simply can’t account for disruption and accelerated change at the scale
we’ve experienced.

3. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
To explore this topic in more detail, I spoke to Rich Clayton, vice president for
product strategy at Oracle Analytics, about the “augmented analytics reset” that’s
underway across the retail industry. This means a fundamental rethink of what
retailers can achieve with analytics and, crucially, how artificial intelligence (AI)
can be used to expand its scope throughout all business processes at all levels.
“In plain English, it’s about putting advanced technology like AI and machine
learning into the analytics workstream,” he tells me.

4. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
"From how we connect to data to how we combine it with other data sources, to how
we consume and share it so that we can all do our jobs better.“
One principle of this “reset” is that store operators can no longer afford to be waiting
for insights derived from analytics to "trickle-down" from centrally-located business
intelligence or analytics units. While we know there’s a global shortage of data
scientists, at the same time, there has been an explosion in the availability of
applications, tools, and platforms that have the potential to put data in the hands of
everyone. This is where retailers should be looking for strategies that will let them
anticipate change and adapt accordingly.

5. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
AUTOMATED INSIGHTS
“As an example – a store manager, when they arrive at the store – their cell phone
can wake up and know they’re at the store. From there, it can tell them what are
the first three things they need to focus on right away.”
This could mean alerts that inventory issues are predicted, or that data suggests a
particular product is going to be popular that day. The manager can then go
about their day-to-day activities, such as inventory management, merchandising,
display coordination, or interacting with supply chain partners, based on the
insights they’ve been given.

6. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
“An analytic reset starts by reflecting on current processes,” Clayton says. This means
examining the data platforms that are currently used through the lens of the
changed business priorities.
“Once we reflect on our current state, we then begin to think about restoring order
and focus on our plans in the short term. What insights, predictions, or analytic
experiences do we need to focus on to meet the new normal?”
Only when that’s fully understood should we start to think about how these changes
might affect our long-term strategy, Clayton suggests.

7. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
SUSTAINABLE AND CONNECTED EXPERIENCES
Navigating this reset should involve creating strategies to tackle three challenges – creating connected
customer experiences, improving the integrity and efficiency of supply chains, and using data to build
sustainable profit models.
"Connected customer experience is probably the number one challenge today because of how buying
behavior is changing between online and offline," he tells me.
In fact, this aligns closely with the need to create sustainable profit models, which, if they are managed
properly, will emerge from the connected experience. For example, retailers can look to correlate
customer activity across online and offline channels to build a more complete picture of their behavior.
Products and services can then be offered with the aim of building and maintaining customer loyalty
while also generating profit.

8. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
“Those are two things that are sometimes seen as being at odds with each other, and I think that
deeper insights through AI can help overcome some of those challenges.”
Managing returns in e-commerce is a great example of an area where new thinking could have a
dramatic impact. The dramatic upscaling in the amount of online shopping being done by
consumers – up to 10 years of growth in 18 months, by some estimates – means retailers are
dealing with far larger quantities of returned goods, generating waste and expense.
Artificial intelligence can be used to predict where these returns are most likely to occur – what
items will most frequently be returned, by which customers, in what regions. It can also help
identify when returns are potentially fraudulent.

9. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
“If you’re just going to accept everything that’s returned, you're probably going to lose money," says
Clayton. "But AI can predict which items are most likely to be returned and make recommendations
about what can be done with some of those volatile items.“
Another area where analytics has been used to predict the effect of dramatic societal changes has been
anticipating where staff shortages might be caused by older retail workers deciding to take early
retirement rather than return to the shop floor post-covid.
To get to the point where AI can help with decisions like these, many retail organizations are going to
need to overcome problems caused by siloed data – data that’s been collected and stored for a specific
purpose but not made available to the wider business, for use in innovative ways. All this can be
achieved by taking the holistic approach to data strategy – where the value of data is considered across
all business functions – that Clayton is advocating as part of the "reset."

10. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
New ways of disseminating the insights gleaned from data need to be developed too, and here
natural language processing (NPL) – an Ai technology that enables machines to express insights
in natural, human language, could be extremely valuable.
Store managers can't be expected to be data scientists – show them charts and dashboards, and
the insights might not be immediately obvious to them. But the technology exists that can take
data – whether it's sales data, customer feedback data, or even social media chatter – and use it
to create narratives that can be communicated verbally – like a bespoke podcast tailored
specifically for the person it’s intended for. This would make situations like the one mentioned at
the start of this article – where the store manager is automatically informed what their priorities
should be when they arrive at work in the morning – a real possibility.

11. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
Speed, scope, and scale are the keywords that retail data strategists need to keep in mind
when thinking about implementing these types of changes or "resets.“
There needs to be the capability to trial and launch data initiatives quickly to keep up with
the fast-paced change because insights that seem critical today might not be relevant to
the situation tomorrow. Scope means always thinking about new data sources that can be
included and new channels that insights can be applied through. Scope means making sure
every aspect of operations and business processes is influenced by the output of AI-
augmented analytics.

12. © 2021 Bernard Marr, Bernard Marr & Co. All rights reserved
Retailers have found themselves at the vanguard of an expedition into new
territory – simply because there is no rule book for managing the widespread
change in customer behavior that we see today. Those that are willing to invest
in innovation and the rollout of holistic, AI-driven analytics strategies are best
placed to achieve continued growth in these fast-changing times.

13. © 2021 Bernard Marr , Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker,
futurist, and a strategic business & technology advisor to governments and
companies. He helps organisations improve their business performance, use data
more intelligently, and understand the implications of new technologies such as
artificial intelligence, big data, blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is
a frequent contributor to the World Economic Forum and writes a regular column for
Forbes. Every day Bernard actively engages his 1.5 million social media followers
and shares content that reaches millions of readers.

14. hello@bernardmarr.com
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